Prosper Loans Exploration by Gabor Sar
Analysis
Data Overview
## [1] 113937 81## [1] "ListingKey"
## [2] "ListingNumber"
## [3] "ListingCreationDate"
## [4] "CreditGrade"
## [5] "Term"
## [6] "LoanStatus"
## [7] "ClosedDate"
## [8] "BorrowerAPR"
## [9] "BorrowerRate"
## [10] "LenderYield"
## [11] "EstimatedEffectiveYield"
## [12] "EstimatedLoss"
## [13] "EstimatedReturn"
## [14] "ProsperRating..numeric."
## [15] "ProsperRating..Alpha."
## [16] "ProsperScore"
## [17] "ListingCategory..numeric."
## [18] "BorrowerState"
## [19] "Occupation"
## [20] "EmploymentStatus"
## [21] "EmploymentStatusDuration"
## [22] "IsBorrowerHomeowner"
## [23] "CurrentlyInGroup"
## [24] "GroupKey"
## [25] "DateCreditPulled"
## [26] "CreditScoreRangeLower"
## [27] "CreditScoreRangeUpper"
## [28] "FirstRecordedCreditLine"
## [29] "CurrentCreditLines"
## [30] "OpenCreditLines"
## [31] "TotalCreditLinespast7years"
## [32] "OpenRevolvingAccounts"
## [33] "OpenRevolvingMonthlyPayment"
## [34] "InquiriesLast6Months"
## [35] "TotalInquiries"
## [36] "CurrentDelinquencies"
## [37] "AmountDelinquent"
## [38] "DelinquenciesLast7Years"
## [39] "PublicRecordsLast10Years"
## [40] "PublicRecordsLast12Months"
## [41] "RevolvingCreditBalance"
## [42] "BankcardUtilization"
## [43] "AvailableBankcardCredit"
## [44] "TotalTrades"
## [45] "TradesNeverDelinquent..percentage."
## [46] "TradesOpenedLast6Months"
## [47] "DebtToIncomeRatio"
## [48] "IncomeRange"
## [49] "IncomeVerifiable"
## [50] "StatedMonthlyIncome"
## [51] "LoanKey"
## [52] "TotalProsperLoans"
## [53] "TotalProsperPaymentsBilled"
## [54] "OnTimeProsperPayments"
## [55] "ProsperPaymentsLessThanOneMonthLate"
## [56] "ProsperPaymentsOneMonthPlusLate"
## [57] "ProsperPrincipalBorrowed"
## [58] "ProsperPrincipalOutstanding"
## [59] "ScorexChangeAtTimeOfListing"
## [60] "LoanCurrentDaysDelinquent"
## [61] "LoanFirstDefaultedCycleNumber"
## [62] "LoanMonthsSinceOrigination"
## [63] "LoanNumber"
## [64] "LoanOriginalAmount"
## [65] "LoanOriginationDate"
## [66] "LoanOriginationQuarter"
## [67] "MemberKey"
## [68] "MonthlyLoanPayment"
## [69] "LP_CustomerPayments"
## [70] "LP_CustomerPrincipalPayments"
## [71] "LP_InterestandFees"
## [72] "LP_ServiceFees"
## [73] "LP_CollectionFees"
## [74] "LP_GrossPrincipalLoss"
## [75] "LP_NetPrincipalLoss"
## [76] "LP_NonPrincipalRecoverypayments"
## [77] "PercentFunded"
## [78] "Recommendations"
## [79] "InvestmentFromFriendsCount"
## [80] "InvestmentFromFriendsAmount"
## [81] "Investors"There are 113937 loans in the dataset with 81 features.
## 'data.frame': 113937 obs. of 81 variables:
## $ ListingKey : Factor w/ 113066 levels "00003546482094282EF90E5",..: 7180 7193 6647 6669 6686 6689 6699 6706 6687 6687 ...
## $ ListingNumber : int 193129 1209647 81716 658116 909464 1074836 750899 768193 1023355 1023355 ...
## $ ListingCreationDate : Factor w/ 113064 levels "2005-11-09 20:44:28.847000000",..: 14184 111894 6429 64760 85967 100310 72556 74019 97834 97834 ...
## $ CreditGrade : Factor w/ 9 levels "","A","AA","B",..: 5 1 8 1 1 1 1 1 1 1 ...
## $ Term : int 36 36 36 36 36 60 36 36 36 36 ...
## $ LoanStatus : Factor w/ 12 levels "Cancelled","Chargedoff",..: 3 4 3 4 4 4 4 4 4 4 ...
## $ ClosedDate : Factor w/ 2803 levels "","2005-11-25 00:00:00",..: 1138 1 1263 1 1 1 1 1 1 1 ...
## $ BorrowerAPR : num 0.165 0.12 0.283 0.125 0.246 ...
## $ BorrowerRate : num 0.158 0.092 0.275 0.0974 0.2085 ...
## $ LenderYield : num 0.138 0.082 0.24 0.0874 0.1985 ...
## $ EstimatedEffectiveYield : num NA 0.0796 NA 0.0849 0.1832 ...
## $ EstimatedLoss : num NA 0.0249 NA 0.0249 0.0925 ...
## $ EstimatedReturn : num NA 0.0547 NA 0.06 0.0907 ...
## $ ProsperRating..numeric. : int NA 6 NA 6 3 5 2 4 7 7 ...
## $ ProsperRating..Alpha. : Factor w/ 8 levels "","A","AA","B",..: 1 2 1 2 6 4 7 5 3 3 ...
## $ ProsperScore : num NA 7 NA 9 4 10 2 4 9 11 ...
## $ ListingCategory..numeric. : int 0 2 0 16 2 1 1 2 7 7 ...
## $ BorrowerState : Factor w/ 52 levels "","AK","AL","AR",..: 7 7 12 12 25 34 18 6 16 16 ...
## $ Occupation : Factor w/ 68 levels "","Accountant/CPA",..: 37 43 37 52 21 43 50 29 24 24 ...
## $ EmploymentStatus : Factor w/ 9 levels "","Employed",..: 9 2 4 2 2 2 2 2 2 2 ...
## $ EmploymentStatusDuration : int 2 44 NA 113 44 82 172 103 269 269 ...
## $ IsBorrowerHomeowner : Factor w/ 2 levels "False","True": 2 1 1 2 2 2 1 1 2 2 ...
## $ CurrentlyInGroup : Factor w/ 2 levels "False","True": 2 1 2 1 1 1 1 1 1 1 ...
## $ GroupKey : Factor w/ 707 levels "","00343376901312423168731",..: 1 1 335 1 1 1 1 1 1 1 ...
## $ DateCreditPulled : Factor w/ 112992 levels "2005-11-09 00:30:04.487000000",..: 14347 111883 6446 64724 85857 100382 72500 73937 97888 97888 ...
## $ CreditScoreRangeLower : int 640 680 480 800 680 740 680 700 820 820 ...
## $ CreditScoreRangeUpper : int 659 699 499 819 699 759 699 719 839 839 ...
## $ FirstRecordedCreditLine : Factor w/ 11586 levels "","1947-08-24 00:00:00",..: 8639 6617 8927 2247 9498 497 8265 7685 5543 5543 ...
## $ CurrentCreditLines : int 5 14 NA 5 19 21 10 6 17 17 ...
## $ OpenCreditLines : int 4 14 NA 5 19 17 7 6 16 16 ...
## $ TotalCreditLinespast7years : int 12 29 3 29 49 49 20 10 32 32 ...
## $ OpenRevolvingAccounts : int 1 13 0 7 6 13 6 5 12 12 ...
## $ OpenRevolvingMonthlyPayment : num 24 389 0 115 220 1410 214 101 219 219 ...
## $ InquiriesLast6Months : int 3 3 0 0 1 0 0 3 1 1 ...
## $ TotalInquiries : num 3 5 1 1 9 2 0 16 6 6 ...
## $ CurrentDelinquencies : int 2 0 1 4 0 0 0 0 0 0 ...
## $ AmountDelinquent : num 472 0 NA 10056 0 ...
## $ DelinquenciesLast7Years : int 4 0 0 14 0 0 0 0 0 0 ...
## $ PublicRecordsLast10Years : int 0 1 0 0 0 0 0 1 0 0 ...
## $ PublicRecordsLast12Months : int 0 0 NA 0 0 0 0 0 0 0 ...
## $ RevolvingCreditBalance : num 0 3989 NA 1444 6193 ...
## $ BankcardUtilization : num 0 0.21 NA 0.04 0.81 0.39 0.72 0.13 0.11 0.11 ...
## $ AvailableBankcardCredit : num 1500 10266 NA 30754 695 ...
## $ TotalTrades : num 11 29 NA 26 39 47 16 10 29 29 ...
## $ TradesNeverDelinquent..percentage. : num 0.81 1 NA 0.76 0.95 1 0.68 0.8 1 1 ...
## $ TradesOpenedLast6Months : num 0 2 NA 0 2 0 0 0 1 1 ...
## $ DebtToIncomeRatio : num 0.17 0.18 0.06 0.15 0.26 0.36 0.27 0.24 0.25 0.25 ...
## $ IncomeRange : Factor w/ 8 levels "$0","$1-24,999",..: 4 5 7 4 3 3 4 4 4 4 ...
## $ IncomeVerifiable : Factor w/ 2 levels "False","True": 2 2 2 2 2 2 2 2 2 2 ...
## $ StatedMonthlyIncome : num 3083 6125 2083 2875 9583 ...
## $ LoanKey : Factor w/ 113066 levels "00003683605746079487FF7",..: 100337 69837 46303 70776 71387 86505 91250 5425 908 908 ...
## $ TotalProsperLoans : int NA NA NA NA 1 NA NA NA NA NA ...
## $ TotalProsperPaymentsBilled : int NA NA NA NA 11 NA NA NA NA NA ...
## $ OnTimeProsperPayments : int NA NA NA NA 11 NA NA NA NA NA ...
## $ ProsperPaymentsLessThanOneMonthLate: int NA NA NA NA 0 NA NA NA NA NA ...
## $ ProsperPaymentsOneMonthPlusLate : int NA NA NA NA 0 NA NA NA NA NA ...
## $ ProsperPrincipalBorrowed : num NA NA NA NA 11000 NA NA NA NA NA ...
## $ ProsperPrincipalOutstanding : num NA NA NA NA 9948 ...
## $ ScorexChangeAtTimeOfListing : int NA NA NA NA NA NA NA NA NA NA ...
## $ LoanCurrentDaysDelinquent : int 0 0 0 0 0 0 0 0 0 0 ...
## $ LoanFirstDefaultedCycleNumber : int NA NA NA NA NA NA NA NA NA NA ...
## $ LoanMonthsSinceOrigination : int 78 0 86 16 6 3 11 10 3 3 ...
## $ LoanNumber : int 19141 134815 6466 77296 102670 123257 88353 90051 121268 121268 ...
## $ LoanOriginalAmount : int 9425 10000 3001 10000 15000 15000 3000 10000 10000 10000 ...
## $ LoanOriginationDate : Factor w/ 1873 levels "2005-11-15 00:00:00",..: 426 1866 260 1535 1757 1821 1649 1666 1813 1813 ...
## $ LoanOriginationQuarter : Factor w/ 33 levels "Q1 2006","Q1 2007",..: 18 8 2 32 24 33 16 16 33 33 ...
## $ MemberKey : Factor w/ 90831 levels "00003397697413387CAF966",..: 11071 10302 33781 54939 19465 48037 60448 40951 26129 26129 ...
## $ MonthlyLoanPayment : num 330 319 123 321 564 ...
## $ LP_CustomerPayments : num 11396 0 4187 5143 2820 ...
## $ LP_CustomerPrincipalPayments : num 9425 0 3001 4091 1563 ...
## $ LP_InterestandFees : num 1971 0 1186 1052 1257 ...
## $ LP_ServiceFees : num -133.2 0 -24.2 -108 -60.3 ...
## $ LP_CollectionFees : num 0 0 0 0 0 0 0 0 0 0 ...
## $ LP_GrossPrincipalLoss : num 0 0 0 0 0 0 0 0 0 0 ...
## $ LP_NetPrincipalLoss : num 0 0 0 0 0 0 0 0 0 0 ...
## $ LP_NonPrincipalRecoverypayments : num 0 0 0 0 0 0 0 0 0 0 ...
## $ PercentFunded : num 1 1 1 1 1 1 1 1 1 1 ...
## $ Recommendations : int 0 0 0 0 0 0 0 0 0 0 ...
## $ InvestmentFromFriendsCount : int 0 0 0 0 0 0 0 0 0 0 ...
## $ InvestmentFromFriendsAmount : num 0 0 0 0 0 0 0 0 0 0 ...
## $ Investors : int 258 1 41 158 20 1 1 1 1 1 ...ListingCategory..numeric. contains integer numbers. Converting it to a factor could be very usefull.
I am going to map the following numbers to the following levels:
| Number | Level |
|---|---|
| 0 | Not Available |
| 1 | Debt Consolidation |
| 2 | Home Improvement |
| 3 | Business |
| 4 | Personal Loan |
| 5 | Student Use |
| 6 | Auto |
| 7 | Other |
| 8 | Baby&Adoption |
| 9 | Boat |
| 10 | Cosmetic Procedure |
| 11 | Engagement Ring |
| 12 | Green Loans |
| 13 | Household Expenses |
| 14 | Large Purchases |
| 15 | Medical/Dental |
| 16 | Motorcycle |
| 17 | RV |
| 18 | Taxes |
| 19 | Vacation |
| 20 | Wedding Loans |
ListingCreationDate, ClosedDate and LoanOriginationDate are factors. Converting them to dates could make plotting by date easier.
Univariate Analysis
## ListingKey ListingNumber ListingCreationDate
## 17A93590655669644DB4C06: 6 Min. : 4 Min. :2005-11-09
## 349D3587495831350F0F648: 4 1st Qu.: 400919 1st Qu.:2008-09-19
## 47C1359638497431975670B: 4 Median : 600554 Median :2012-06-16
## 8474358854651984137201C: 4 Mean : 627886 Mean :2011-07-08
## DE8535960513435199406CE: 4 3rd Qu.: 892634 3rd Qu.:2013-09-09
## 04C13599434217079754AEE: 3 Max. :1255725 Max. :2014-03-10
## (Other) :113912
## CreditGrade Term LoanStatus
## :84984 Min. :12.00 Current :56576
## C : 5649 1st Qu.:36.00 Completed :38074
## D : 5153 Median :36.00 Chargedoff :11992
## B : 4389 Mean :40.83 Defaulted : 5018
## AA : 3509 3rd Qu.:36.00 Past Due (1-15 days) : 806
## HR : 3508 Max. :60.00 Past Due (31-60 days): 363
## (Other): 6745 (Other) : 1108
## ClosedDate BorrowerAPR BorrowerRate LenderYield
## Min. :2005-11-25 Min. :0.00653 Min. :0.0000 Min. :-0.0100
## 1st Qu.:2009-07-14 1st Qu.:0.15629 1st Qu.:0.1340 1st Qu.: 0.1242
## Median :2011-04-05 Median :0.20976 Median :0.1840 Median : 0.1730
## Mean :2011-03-07 Mean :0.21883 Mean :0.1928 Mean : 0.1827
## 3rd Qu.:2013-01-30 3rd Qu.:0.28381 3rd Qu.:0.2500 3rd Qu.: 0.2400
## Max. :2014-03-10 Max. :0.51229 Max. :0.4975 Max. : 0.4925
## NA's :58848 NA's :25
## EstimatedEffectiveYield EstimatedLoss EstimatedReturn
## Min. :-0.183 Min. :0.005 Min. :-0.183
## 1st Qu.: 0.116 1st Qu.:0.042 1st Qu.: 0.074
## Median : 0.162 Median :0.072 Median : 0.092
## Mean : 0.169 Mean :0.080 Mean : 0.096
## 3rd Qu.: 0.224 3rd Qu.:0.112 3rd Qu.: 0.117
## Max. : 0.320 Max. :0.366 Max. : 0.284
## NA's :29084 NA's :29084 NA's :29084
## ProsperRating..numeric. ProsperRating..Alpha. ProsperScore
## Min. :1.000 :29084 Min. : 1.00
## 1st Qu.:3.000 C :18345 1st Qu.: 4.00
## Median :4.000 B :15581 Median : 6.00
## Mean :4.072 A :14551 Mean : 5.95
## 3rd Qu.:5.000 D :14274 3rd Qu.: 8.00
## Max. :7.000 E : 9795 Max. :11.00
## NA's :29084 (Other):12307 NA's :29084
## ListingCategory..numeric. BorrowerState
## Min. : 0.000 CA :14717
## 1st Qu.: 1.000 TX : 6842
## Median : 1.000 NY : 6729
## Mean : 2.774 FL : 6720
## 3rd Qu.: 3.000 IL : 5921
## Max. :20.000 : 5515
## (Other):67493
## Occupation EmploymentStatus
## Other :28617 Employed :67322
## Professional :13628 Full-time :26355
## Computer Programmer : 4478 Self-employed: 6134
## Executive : 4311 Not available: 5347
## Teacher : 3759 Other : 3806
## Administrative Assistant: 3688 : 2255
## (Other) :55456 (Other) : 2718
## EmploymentStatusDuration IsBorrowerHomeowner CurrentlyInGroup
## Min. : 0.00 False:56459 False:101218
## 1st Qu.: 26.00 True :57478 True : 12719
## Median : 67.00
## Mean : 96.07
## 3rd Qu.:137.00
## Max. :755.00
## NA's :7625
## GroupKey DateCreditPulled
## :100596 2013-12-23 09:38:12: 6
## 783C3371218786870A73D20: 1140 2013-11-21 09:09:41: 4
## 3D4D3366260257624AB272D: 916 2013-12-06 05:43:16: 4
## 6A3B336601725506917317E: 698 2014-01-14 20:17:49: 4
## FEF83377364176536637E50: 611 2014-02-09 12:14:41: 4
## C9643379247860156A00EC0: 342 2013-09-27 22:04:54: 3
## (Other) : 9634 (Other) :113912
## CreditScoreRangeLower CreditScoreRangeUpper
## Min. : 0.0 Min. : 19.0
## 1st Qu.:660.0 1st Qu.:679.0
## Median :680.0 Median :699.0
## Mean :685.6 Mean :704.6
## 3rd Qu.:720.0 3rd Qu.:739.0
## Max. :880.0 Max. :899.0
## NA's :591 NA's :591
## FirstRecordedCreditLine CurrentCreditLines OpenCreditLines
## : 697 Min. : 0.00 Min. : 0.00
## 1993-12-01 00:00:00: 185 1st Qu.: 7.00 1st Qu.: 6.00
## 1994-11-01 00:00:00: 178 Median :10.00 Median : 9.00
## 1995-11-01 00:00:00: 168 Mean :10.32 Mean : 9.26
## 1990-04-01 00:00:00: 161 3rd Qu.:13.00 3rd Qu.:12.00
## 1995-03-01 00:00:00: 159 Max. :59.00 Max. :54.00
## (Other) :112389 NA's :7604 NA's :7604
## TotalCreditLinespast7years OpenRevolvingAccounts
## Min. : 2.00 Min. : 0.00
## 1st Qu.: 17.00 1st Qu.: 4.00
## Median : 25.00 Median : 6.00
## Mean : 26.75 Mean : 6.97
## 3rd Qu.: 35.00 3rd Qu.: 9.00
## Max. :136.00 Max. :51.00
## NA's :697
## OpenRevolvingMonthlyPayment InquiriesLast6Months TotalInquiries
## Min. : 0.0 Min. : 0.000 Min. : 0.000
## 1st Qu.: 114.0 1st Qu.: 0.000 1st Qu.: 2.000
## Median : 271.0 Median : 1.000 Median : 4.000
## Mean : 398.3 Mean : 1.435 Mean : 5.584
## 3rd Qu.: 525.0 3rd Qu.: 2.000 3rd Qu.: 7.000
## Max. :14985.0 Max. :105.000 Max. :379.000
## NA's :697 NA's :1159
## CurrentDelinquencies AmountDelinquent DelinquenciesLast7Years
## Min. : 0.0000 Min. : 0.0 Min. : 0.000
## 1st Qu.: 0.0000 1st Qu.: 0.0 1st Qu.: 0.000
## Median : 0.0000 Median : 0.0 Median : 0.000
## Mean : 0.5921 Mean : 984.5 Mean : 4.155
## 3rd Qu.: 0.0000 3rd Qu.: 0.0 3rd Qu.: 3.000
## Max. :83.0000 Max. :463881.0 Max. :99.000
## NA's :697 NA's :7622 NA's :990
## PublicRecordsLast10Years PublicRecordsLast12Months RevolvingCreditBalance
## Min. : 0.0000 Min. : 0.000 Min. : 0
## 1st Qu.: 0.0000 1st Qu.: 0.000 1st Qu.: 3121
## Median : 0.0000 Median : 0.000 Median : 8549
## Mean : 0.3126 Mean : 0.015 Mean : 17599
## 3rd Qu.: 0.0000 3rd Qu.: 0.000 3rd Qu.: 19521
## Max. :38.0000 Max. :20.000 Max. :1435667
## NA's :697 NA's :7604 NA's :7604
## BankcardUtilization AvailableBankcardCredit TotalTrades
## Min. :0.000 Min. : 0 Min. : 0.00
## 1st Qu.:0.310 1st Qu.: 880 1st Qu.: 15.00
## Median :0.600 Median : 4100 Median : 22.00
## Mean :0.561 Mean : 11210 Mean : 23.23
## 3rd Qu.:0.840 3rd Qu.: 13180 3rd Qu.: 30.00
## Max. :5.950 Max. :646285 Max. :126.00
## NA's :7604 NA's :7544 NA's :7544
## TradesNeverDelinquent..percentage. TradesOpenedLast6Months
## Min. :0.000 Min. : 0.000
## 1st Qu.:0.820 1st Qu.: 0.000
## Median :0.940 Median : 0.000
## Mean :0.886 Mean : 0.802
## 3rd Qu.:1.000 3rd Qu.: 1.000
## Max. :1.000 Max. :20.000
## NA's :7544 NA's :7544
## DebtToIncomeRatio IncomeRange IncomeVerifiable
## Min. : 0.000 $25,000-49,999:32192 False: 8669
## 1st Qu.: 0.140 $50,000-74,999:31050 True :105268
## Median : 0.220 $100,000+ :17337
## Mean : 0.276 $75,000-99,999:16916
## 3rd Qu.: 0.320 Not displayed : 7741
## Max. :10.010 $1-24,999 : 7274
## NA's :8554 (Other) : 1427
## StatedMonthlyIncome LoanKey TotalProsperLoans
## Min. : 0 CB1B37030986463208432A1: 6 Min. :0.00
## 1st Qu.: 3200 2DEE3698211017519D7333F: 4 1st Qu.:1.00
## Median : 4667 9F4B37043517554537C364C: 4 Median :1.00
## Mean : 5608 D895370150591392337ED6D: 4 Mean :1.42
## 3rd Qu.: 6825 E6FB37073953690388BC56D: 4 3rd Qu.:2.00
## Max. :1750003 0D8F37036734373301ED419: 3 Max. :8.00
## (Other) :113912 NA's :91852
## TotalProsperPaymentsBilled OnTimeProsperPayments
## Min. : 0.00 Min. : 0.00
## 1st Qu.: 9.00 1st Qu.: 9.00
## Median : 16.00 Median : 15.00
## Mean : 22.93 Mean : 22.27
## 3rd Qu.: 33.00 3rd Qu.: 32.00
## Max. :141.00 Max. :141.00
## NA's :91852 NA's :91852
## ProsperPaymentsLessThanOneMonthLate ProsperPaymentsOneMonthPlusLate
## Min. : 0.00 Min. : 0.00
## 1st Qu.: 0.00 1st Qu.: 0.00
## Median : 0.00 Median : 0.00
## Mean : 0.61 Mean : 0.05
## 3rd Qu.: 0.00 3rd Qu.: 0.00
## Max. :42.00 Max. :21.00
## NA's :91852 NA's :91852
## ProsperPrincipalBorrowed ProsperPrincipalOutstanding
## Min. : 0 Min. : 0
## 1st Qu.: 3500 1st Qu.: 0
## Median : 6000 Median : 1627
## Mean : 8472 Mean : 2930
## 3rd Qu.:11000 3rd Qu.: 4127
## Max. :72499 Max. :23451
## NA's :91852 NA's :91852
## ScorexChangeAtTimeOfListing LoanCurrentDaysDelinquent
## Min. :-209.00 Min. : 0.0
## 1st Qu.: -35.00 1st Qu.: 0.0
## Median : -3.00 Median : 0.0
## Mean : -3.22 Mean : 152.8
## 3rd Qu.: 25.00 3rd Qu.: 0.0
## Max. : 286.00 Max. :2704.0
## NA's :95009
## LoanFirstDefaultedCycleNumber LoanMonthsSinceOrigination LoanNumber
## Min. : 0.00 Min. : 0.0 Min. : 1
## 1st Qu.: 9.00 1st Qu.: 6.0 1st Qu.: 37332
## Median :14.00 Median : 21.0 Median : 68599
## Mean :16.27 Mean : 31.9 Mean : 69444
## 3rd Qu.:22.00 3rd Qu.: 65.0 3rd Qu.:101901
## Max. :44.00 Max. :100.0 Max. :136486
## NA's :96985
## LoanOriginalAmount LoanOriginationDate LoanOriginationQuarter
## Min. : 1000 Min. :2005-11-15 Q4 2013:14450
## 1st Qu.: 4000 1st Qu.:2008-10-02 Q1 2014:12172
## Median : 6500 Median :2012-06-26 Q3 2013: 9180
## Mean : 8337 Mean :2011-07-21 Q2 2013: 7099
## 3rd Qu.:12000 3rd Qu.:2013-09-18 Q3 2012: 5632
## Max. :35000 Max. :2014-03-12 Q2 2012: 5061
## (Other):60343
## MemberKey MonthlyLoanPayment LP_CustomerPayments
## 63CA34120866140639431C9: 9 Min. : 0.0 Min. : -2.35
## 16083364744933457E57FB9: 8 1st Qu.: 131.6 1st Qu.: 1005.76
## 3A2F3380477699707C81385: 8 Median : 217.7 Median : 2583.83
## 4D9C3403302047712AD0CDD: 8 Mean : 272.5 Mean : 4183.08
## 739C338135235294782AE75: 8 3rd Qu.: 371.6 3rd Qu.: 5548.40
## 7E1733653050264822FAA3D: 8 Max. :2251.5 Max. :40702.39
## (Other) :113888
## LP_CustomerPrincipalPayments LP_InterestandFees LP_ServiceFees
## Min. : 0.0 Min. : -2.35 Min. :-664.87
## 1st Qu.: 500.9 1st Qu.: 274.87 1st Qu.: -73.18
## Median : 1587.5 Median : 700.84 Median : -34.44
## Mean : 3105.5 Mean : 1077.54 Mean : -54.73
## 3rd Qu.: 4000.0 3rd Qu.: 1458.54 3rd Qu.: -13.92
## Max. :35000.0 Max. :15617.03 Max. : 32.06
##
## LP_CollectionFees LP_GrossPrincipalLoss LP_NetPrincipalLoss
## Min. :-9274.75 Min. : -94.2 Min. : -954.5
## 1st Qu.: 0.00 1st Qu.: 0.0 1st Qu.: 0.0
## Median : 0.00 Median : 0.0 Median : 0.0
## Mean : -14.24 Mean : 700.4 Mean : 681.4
## 3rd Qu.: 0.00 3rd Qu.: 0.0 3rd Qu.: 0.0
## Max. : 0.00 Max. :25000.0 Max. :25000.0
##
## LP_NonPrincipalRecoverypayments PercentFunded Recommendations
## Min. : 0.00 Min. :0.7000 Min. : 0.00000
## 1st Qu.: 0.00 1st Qu.:1.0000 1st Qu.: 0.00000
## Median : 0.00 Median :1.0000 Median : 0.00000
## Mean : 25.14 Mean :0.9986 Mean : 0.04803
## 3rd Qu.: 0.00 3rd Qu.:1.0000 3rd Qu.: 0.00000
## Max. :21117.90 Max. :1.0125 Max. :39.00000
##
## InvestmentFromFriendsCount InvestmentFromFriendsAmount Investors
## Min. : 0.00000 Min. : 0.00 Min. : 1.00
## 1st Qu.: 0.00000 1st Qu.: 0.00 1st Qu.: 2.00
## Median : 0.00000 Median : 0.00 Median : 44.00
## Mean : 0.02346 Mean : 16.55 Mean : 80.48
## 3rd Qu.: 0.00000 3rd Qu.: 0.00 3rd Qu.: 115.00
## Max. :33.00000 Max. :25000.00 Max. :1189.00
##
## ListingCategory
## Debt Consolidation:58308
## Not Available :16965
## Other :10494
## Home Improvement : 7433
## Business : 7189
## Auto : 2572
## (Other) :10976Most of the loans have current or completed status.
The minimum estimated return is -0.183. The median estimated return is 0.092, and the maximum is 0.284. This seems pretty balanced.
Most of the loans (51%) for debt consolidation.
At least 88% percent of the borrowers employed, and the median of their employment duration is 67 months.
The median upper credit score range is 699, and the maximum is 899. The lower and upper credit score range values are very close to each other.
The median stated monthly income is $4,667, and the maximum is $1,750,003. This is a big difference. 92% of the incomes are verifiable.
The amount of loans are between $1,000 and $35,000, and the median is $6,500.
The median monthly loan payment is $217.7, and the maximum is $2,251.5. This is also a big difference.
Loan Original Amount
## 4000 15000 10000 5000 2000 3000 25000 20000 1000
## 14333 12407 11106 6990 6067 5749 3630 3291 3206
## 2500 (Other)
## 2992 44166
Most of the loan amount values are between $1,000 and $10,000. There are some values that are more frequent than the others. Based on the list of the ten most frequent values, it seems like approximately every five thousandth. Setting the binwidth to 5000 shows a decreasing trend.
Loan Origination Date
There is an increasing trend in the number of loans from 2006 to late 2008 and from late 2009 to 2014, and there is a gap between late 2008 and late 2009. Enlarging that timeframe shows that there were almost 0 loans registered in an approximately 10-months period. The most likely reason for this anomaly is the subprime mortgage crisis.
Term
##
## 12 36 60
## 1614 87778 2454577% of the loans last 36 months (3 years), 21% last 60 months (5 years) and 1% last 12 months (1 year).
Monthly Loan Payment
##
## FALSE TRUE
## 113002 935##
## Cancelled Chargedoff Completed
## 0 0 800
## Current Defaulted FinalPaymentInProgress
## 0 131 4
## Past Due (>120 days) Past Due (1-15 days) Past Due (16-30 days)
## 0 0 0
## Past Due (31-60 days) Past Due (61-90 days) Past Due (91-120 days)
## 0 0 0The majority of the monthly payments are between $0 and $500. There are some outliers. 935 loans have a monthly payment of $0. All of those loans are completed, defaulted or the final payment is in progress.
Stated Monthly Income
The histogram of monthly incomes shows a serious outlier issue. This supports my feelings about the big difference between the median ($4,667), and the maximum ($1,750,003).
##
## FALSE TRUE
## 112543 1394Limiting the values to the .99 quantile and setting the binwidth to 150 shows a much better, positively skewed normal distribution. The only thing that does not seem obvious is the high frequency (1394) of the 0 values.
##
## Not Available Debt Consolidation Home Improvement
## 238 358 47
## Business Personal Loan Student Use
## 249 121 67
## Auto Other Baby&Adoption
## 28 183 1
## Boat Cosmetic Procedure Engagement Ring
## 1 1 4
## Green Loans Household Expenses Large Purchases
## 2 56 6
## Medical/Dental Motorcycle RV
## 17 0 0
## Taxes Vacation Wedding Loans
## 4 8 3Listing category does not explain the zero values.
##
## Cancelled Chargedoff Completed
## 1 347 677
## Current Defaulted FinalPaymentInProgress
## 259 80 0
## Past Due (>120 days) Past Due (1-15 days) Past Due (16-30 days)
## 1 11 5
## Past Due (31-60 days) Past Due (61-90 days) Past Due (91-120 days)
## 3 7 3Most of these loans are completed, charged off or defaulted, but still 259 of them are current.
##
## False True
## 1330 64Only 64 of these loans contains a verifiable monthly income.
Debt to Income Ratio
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 0.000 0.140 0.220 0.276 0.320 10.010 8554##
## FALSE TRUE
## 104948 435Most of the debt income ratio values are between 0.14 and 0.32. There are some outliers. The maximum is 10.01, and there are 435 values greater than 2.5.
Credit Score Range Lower
##
## 0 360 420 440 460 480 500 520 540 560 580 600
## 133 1 5 36 141 346 554 1593 1474 1357 1125 3602
## 620 640 660 680 700 720 740 760 780 800 820 840
## 4172 12199 16366 16492 15471 12923 9267 6606 4624 2644 1409 567
## 860 880
## 212 27
Most of the lower credit score range values are between 600 and 800. There are some outliers.
Credit Score Range Upper
##
## 19 379 439 459 479 499 519 539 559 579 599 619
## 133 1 5 36 141 346 554 1593 1474 1357 1125 3602
## 639 659 679 699 719 739 759 779 799 819 839 859
## 4172 12199 16366 16492 15471 12923 9267 6606 4624 2644 1409 567
## 879 899
## 212 27
Most of the upper credit score range values are between 600 and 800. There are some outliers.
This data seems almost the same as the lower credit score range values.
Borrower Rate
## Source: local data frame [2,294 x 2]
##
## BorrowerRate count
## 1 0.3177 3672
## 2 0.3500 1905
## 3 0.3199 1651
## 4 0.2900 1508
## 5 0.2699 1319
## 6 0.1500 1182
## 7 0.1400 1035
## 8 0.1099 949
## 9 0.2000 907
## 10 0.1585 806
## .. ... ...Most borrower rates are between 0.1 and 0.3. The values at 0.32 and 0.35 are unexpectedly frequent.
Borrower APR
## Source: local data frame [6,678 x 2]
##
## BorrowerAPR count
## 1 0.35797 3672
## 2 0.35643 1644
## 3 0.37453 1260
## 4 0.30532 902
## 5 0.29510 747
## 6 0.35356 721
## 7 0.29776 707
## 8 0.15833 652
## 9 0.24246 605
## 10 0.24758 601
## .. ... ...Most borrower APR values are between 0.1 and 0.3. The values at 0.32 and 0.35 are unexpectedly frequent.
It seems like there is a strong relationship between borrower rate and borrower APR.
I would like to know if there is any explanation of those unexpectedly frequent values.
Employment Status
##
## Employed Full-time Not available Not employed
## 2255 67322 26355 5347 835
## Other Part-time Retired Self-employed
## 3806 1088 795 613489% of the borrowers employed or retired (Employed, Full-time, Part-time, Retired, Self-employed), <1% Not employed, and there is no useful employment information about 10% of them (NA, Not available, Other).
Employment Status Duration
Most of the employment status durations are between 0 and 200 months, and the distribution shows a decreasing trend.
Estimated Return
##
## FALSE TRUE
## 84658 195Most of the estimated returns are between 0.05 and 0.15. There are some outliers, and 195 values are negative.
Listing Category
##
## Not Available Debt Consolidation Home Improvement
## 16965 58308 7433
## Business Personal Loan Student Use
## 7189 2395 756
## Auto Other Baby&Adoption
## 2572 10494 199
## Boat Cosmetic Procedure Engagement Ring
## 85 91 217
## Green Loans Household Expenses Large Purchases
## 59 1996 876
## Medical/Dental Motorcycle RV
## 1522 304 52
## Taxes Vacation Wedding Loans
## 885 768 771
Most loans have a listing category of debt consolidation. A lot of loans does not have a useful listing category (Not Available, Other).
Loan Status
##
## Cancelled Chargedoff Completed
## 5 11992 38074
## Current Defaulted FinalPaymentInProgress
## 56576 5018 205
## Past Due (>120 days) Past Due (1-15 days) Past Due (16-30 days)
## 16 806 265
## Past Due (31-60 days) Past Due (61-90 days) Past Due (91-120 days)
## 363 313 304
Most of the loans have a loan status of current, completed, charged off or defaulted.
Bivariate and Multivariate Analysis
## LoanOriginalAmount Term MonthlyLoanPayment
## LoanOriginalAmount 1.00000000 0.33892746 0.93198368
## Term 0.33892746 1.00000000 0.09102578
## MonthlyLoanPayment 0.93198368 0.09102578 1.00000000
## StatedMonthlyIncome 0.20125947 0.02847925 0.19683026
## DebtToIncomeRatio 0.01011222 -0.01467005 0.02759840
## CreditScoreRangeLower 0.34087445 0.12626345 0.29253205
## CreditScoreRangeUpper 0.34087445 0.12626345 0.29253205
## EmploymentStatusDuration 0.09814935 0.08247591 0.08116016
## EstimatedReturn -0.28611751 0.15250541 -0.25273127
## BorrowerRate -0.32895995 0.02008537 -0.24474235
## BorrowerAPR -0.32288669 -0.01118347 -0.22665287
## StatedMonthlyIncome DebtToIncomeRatio
## LoanOriginalAmount 0.20125947 0.01011222
## Term 0.02847925 -0.01467005
## MonthlyLoanPayment 0.19683026 0.02759840
## StatedMonthlyIncome 1.00000000 -0.12265939
## DebtToIncomeRatio -0.12265939 1.00000000
## CreditScoreRangeLower 0.10790082 -0.01316852
## CreditScoreRangeUpper 0.10790082 -0.01316852
## EmploymentStatusDuration 0.06983037 -0.01160926
## EstimatedReturn -0.07501281 0.08723617
## BorrowerRate -0.08898180 0.06291678
## BorrowerAPR -0.08233849 0.05632742
## CreditScoreRangeLower CreditScoreRangeUpper
## LoanOriginalAmount 0.34087445 0.34087445
## Term 0.12626345 0.12626345
## MonthlyLoanPayment 0.29253205 0.29253205
## StatedMonthlyIncome 0.10790082 0.10790082
## DebtToIncomeRatio -0.01316852 -0.01316852
## CreditScoreRangeLower 1.00000000 1.00000000
## CreditScoreRangeUpper 1.00000000 1.00000000
## EmploymentStatusDuration 0.08113411 0.08113411
## EstimatedReturn -0.34623273 -0.34623273
## BorrowerRate -0.46156668 -0.46156668
## BorrowerAPR -0.42970732 -0.42970732
## EmploymentStatusDuration EstimatedReturn
## LoanOriginalAmount 0.098149347 -0.28611751
## Term 0.082475906 0.15250541
## MonthlyLoanPayment 0.081160161 -0.25273127
## StatedMonthlyIncome 0.069830374 -0.07501281
## DebtToIncomeRatio -0.011609265 0.08723617
## CreditScoreRangeLower 0.081134109 -0.34623273
## CreditScoreRangeUpper 0.081134109 -0.34623273
## EmploymentStatusDuration 1.000000000 -0.03648651
## EstimatedReturn -0.036486506 1.00000000
## BorrowerRate -0.019907440 0.81766987
## BorrowerAPR -0.008588601 0.79427520
## BorrowerRate BorrowerAPR
## LoanOriginalAmount -0.32895995 -0.322886690
## Term 0.02008537 -0.011183469
## MonthlyLoanPayment -0.24474235 -0.226652867
## StatedMonthlyIncome -0.08898180 -0.082338491
## DebtToIncomeRatio 0.06291678 0.056327417
## CreditScoreRangeLower -0.46156668 -0.429707322
## CreditScoreRangeUpper -0.46156668 -0.429707322
## EmploymentStatusDuration -0.01990744 -0.008588601
## EstimatedReturn 0.81766987 0.794275198
## BorrowerRate 1.00000000 0.989823970
## BorrowerAPR 0.98982397 1.000000000Original amount correlates with monthly payment, term, credit score range lower and credit score range upper.
Credit score range lower and credit score range upper are almost identical. Borrower rate and borrower APR also have a very strong realtionship. This means I can omit credit score range upper and borrower APR. I am going to use credit score range lower and borrower rate only.
I would like to see how original amount and monthly payment depends on other variables, and I am also interested in the changes of different variables over the time.
Relationships of Loan Original Amount and Monthly Loan Payment
There are three strong linear relationships between original amount and monthly payment.
This means that original amount cannot describe the variation of monthly payment alone, there must be something else participating in it. Based on the strong correlation between term and monthly payment, and knowing that there are three possible term values, term seems the best next variable to investigate.
##
## Pearson's product-moment correlation
##
## data: MonthlyLoanPayment and LoanOriginalAmount/Term
## t = 1386.25, df = 113935, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.9712849 0.9719350
## sample estimates:
## cor
## 0.9716118Monthly loan payment almost equals to the original amount divided by the term of the loan. Therefore monthly loan payment can be described by original amount and term together.
Let’s see how credit score and borrower rate values affect original amount and monthly payment.
Regardless the relatively strong correlations I cannot find any visible relationship between credit score range lower / borrower rate and original amount / monthly payment.
The last plot seems overplotted, it may worth to revisit it with a lover alpha level.
With the decreased alpha level, I can see some underlying trend, but it is still not enough clean.
Adding term to the plot may help again.
Faceting by term shows a some difference between the previously seen trends.
As term and original amount has a relationship to monthly loan payment adding original amount to the previous plot may make the picture clearer.
Faceting by term and colouring by original amount shows a complex relationship, were both borrower rate, orginal amount and term participates in monthly payment.
I am going to check if stated monthly income can add anything to the picture.
It is clearly visible on this plot (as well), that there are some original amount values that more frequent than the others (approximately every five thousandth), but other than that, this plot cannot help too much.
There is a relationship between monthly loan payment and listing category. Loans for Debt Consolidation have the highest monthly payment, followed by Not Available, Home Improvement, Business and Other.
Changes in Variables Over Time
All the loans before the previously mentioned gap (between late 2008 and late 2009) have a 36-months term. 12-months loans were only occurring for a 2-years period between 2011 and 2013 and were not popular. 60-months loans started to occur at the same time as 12-months loans (in 2011), and there is an increasing trend in the number of those since then.
There is no useful employment status information before late 2006. The Employed category almost replaced the Full Time category in late 2010, this is probably due to a change in the way the data was recorded.
The employment status durations have an increasing trend, but it does not have a strong relation with the changes int the employment status.
Let’s see if there is any relationship between employment status and employment status duration.
There is a relationship between the employment status and the employment status duration. Employed, Full-time, Retired and Self-employed statuses tend to have a higher duration as Not employed or Part-time.
There is no useful listing category information before 2008. New listing categories were introduced in 2008 and 2012 as well. This indicates a change in the way the data was recorded, similarly to listing category.
There is no visible pattern within listing categories.
Final Plots
First Plot
There is a very strong relationship between the term, the original amount and the monthly payment of a loan. The latter can be calculated from the formers. The monthly payment of a loan increases as the term decreases - short term loans have higher monthly payment than long term loans - and increases as the original amount increases.
Second Plot
Monthly loan payment is affected by the borrower rate, higher borrower rate leads to higher monthly payemnt. This relationship is not affected by either the term or the original amount of a loan.
Third Plot
Monthly loan payment vary differently across listing categories. Some categories has more wide monthly payment range (e.g., Debt Consolidation), others has less wide payment range (e.g., Motorcycle).
Reflection
The prosper loan dataset contains 113937 observations of 83 variables from 2006 to 2014. At the beginning of my investigation I was trying to understand the meaning of different variables, find issues with how they stored and how can I make the best use of them. As the dataset contains a lot of variables, it was challenging to decide where to start. Finally, I have chosen to start investigation the variables that best representing a loan: original amount, term and monthly payment, and everything else that can have a relationship with them. First I started to plot each variable one by one to have an initial view about what the dataset contains, and how good the quality of it. I was very surprised when I saw that there were loans with 0 monthly payment, but later I realised that those loans are not current anymore. It was also unexpected that there were no loans in the dataset between late 2008 and late 2009 but after some research I understood that the reason for the gap is the subprime mortgage crisis. Later, during the analysis of the relationships between the different variables I realized that the monthly payment is the most important property of a loan, instead of the original amount as I thought before. I found that the term and the original amount of a loan the most relevant parameters to calculate the monthly payment. Borrower rate has an important role as well, however it was quite hard to visualize that relationship. I also found that there is a difference in the monthly payment, and the variation of the monthly payment across listing categories. Analyzing the changes of the variables over the time shown me that there were a few changes in the way how was the data collected. That made it hard to use some categorical variables, like employment status. The standardization of the mentioned categorical variables would lead to an investigation that could make a better use of them. Investigating the dataset without the loans that are for debt consolidation could give a good picture of the choices of the borrowers. Investigating the loans that are paid by debt consolidation would be useful as well.